The Liaohe Estuary coastal wetland is the northernmost estuary wetland in China， which is an ideal breeding and migration station for many kinds of waterfowl. In recent years， several ecological restoration projects have been carried out to improve the habitat quality in this region. Accurately mapping the landcover types using remote sensing is very important for efficiently evaluating wetland habitat quality and restoration effectiveness. However， most of the classification methods in the Liaohe Estuary were object-oriented， and the mapping results were not fine enough and needed to be updated in years. The applicability of pixel-level method and dense time-series information in this region needed to be further evaluated. This paper relied on Google Earth Engine （GEE） platform， utilized Sentinel-2， Sentinel-1， and topographic multi-source data to extract the features including spectral indices， texture， topography， backscattering， and phenology from the dense time-series vegetation indices. Multi-year sample datasets were generated by field sampling and sample migration， and the pixel-level fine classification mapping from 2018 to 2022 was carried out based on the random forest model. The effects of different features on the classification accuracy were also evaluated. The classification method combining GEE and dense time-series information got an overall classification accuracy of 95.77%. Adding phenology features improved the accuracy most obviously， especially for the mixing between suaeda salsa and reeds， rice， or aquaculture ponds. Adding texture and backscattering features significantly improved the accuracies of aquaculture ponds and construction land. In the last five years， aquaculture ponds decreased while the mudflat and suaeda salsa expanded， which indicated the effects of ecological restoration project. The results provide data and technology supports for analyzing the spatial-temporal changes and driving mechanism of coastal wetland， which is of great significance for strengthening the protection and restoration of wetland ecosystems.